White matter microstructure and executive functions in congenital heart disease from childhood to adulthood: A pooled case-control study

Patterns of WISC-V Performance in Children with Congenital Heart Disease

Congenital heart disease (CHD) is one of the most common congenital birth defects. As surgical and interventional techniques have improved, the mortality has been greatly reduced and the focus has shifted to quality of life and long-term outcomes. The impact of CHD on development and cognition is becoming increasingly recognized. However, more research is needed to understand how children with CHD perform across various cognitive and intellectual domains. This study explored the performance of children with CHD on the newest version of the Wechsler Intelligence Scale for Children compared to normative controls. Children with CHD performed more poorly than normal controls across all indices and most subtests with large effect sizes. Additionally, we explored the patterns of impairment across indices and subtests, as well as the relationships between heard disease variables and WISC-V performance. Block design, Digit Span, and Similarities were the most commonly impaired scores in children with CHD, while Symbol Search, Picture Span, Figure Weights, and Vocabulary were least likely to be impaired.

Cerebral Spinal Fluid Volumetrics and Paralimbic Predictors of Executive Dysfunction in Congenital Heart Disease: A Machine Learning Approach Informing Mechanistic Insights

The relationship between increased cerebral spinal fluid (CSF) ventricular compartments, structural and microstructural dysmaturation, and executive function in patients with congenital heart disease (CHD) is unknown. Here, we leverage a novel machine-learning data-driven technique to delineate interrelationships between CSF ventricular volume, structural and microstructural alterations, clinical risk factors, and sub-domains of executive dysfunction in adolescent CHD patients. We trained random forest regression models to predict measures of executive function (EF) from the NIH Toolbox, the Delis-Kaplan Executive Function System (D-KEFS), and the Behavior Rating Inventory of Executive Function (BRIEF) and across three subdomains of EF - mental flexibility, working memory, and inhibition. We estimated the best parameters for the random forest algorithm via a randomized grid search of parameters using 10-fold cross-validation on the training set only. The best parameters were then used to fit the model on the full training set and validated on the test set. Algorithm performance was measured using root-mean squared-error (RMSE). As predictors, we included patient clinical variables, perioperative clinical measures, microstructural white matter (diffusion tensor imaging- DTI), and structural volumes (volumetric magnetic resonance imaging- MRI). Structural white matter was measured using along-tract diffusivity measures of 13 inter-hemispheric and cortico-association fibers. Structural volumes were measured using FreeSurfer and manual segmentation of key structures. Variable importance was measured by the average Gini-impurity of each feature across all decision trees in which that feature is present in the model, and functional ontology mapping (FOM) was used to measure the degree of overlap in feature importance for each EF subdomain and across subdomains. We found that CSF structural properties (including increased lateral ventricular volume and reduced choroid plexus volumes) in conjunction with proximate cortical projection and paralimbic-related association white matter tracts that straddle the lateral ventricles and distal paralimbic-related subcortical structures (basal ganglia, hippocampus, cerebellum) are predictive of two-specific subdomains of executive dysfunction in CHD patients: cognitive flexibility and inhibition. These findings in conjunction with combined RF models that incorporated clinical risk factors, highlighted important clinical risk factors, including the presence of microbleeds, altered vessel volume, and delayed PDA closure, suggesting that CSF-interstitial fluid clearance, vascular pulsatility, and glymphatic microfluid dynamics may be pathways that are impaired in CHD, providing mechanistic information about the relationship between CSF and executive dysfunction.

A narrative review of the mechanisms and consequences of intermittent hypoxia and the role of advanced analytic techniques in pediatric autonomic disorders

Disorders of autonomic functions are typically characterized by disturbances in multiple organ systems. These disturbances are often comorbidities of common and rare diseases, such as epilepsy, sleep apnea, Rett syndrome, congenital heart disease or mitochondrial diseases. Characteristic of many autonomic disorders is the association with intermittent hypoxia and oxidative stress, which can cause or exaggerate a variety of other autonomic dysfunctions, making the treatment and management of these syndromes very complex. In this review we discuss the cellular mechanisms by which intermittent hypoxia can trigger a cascade of molecular, cellular and network events that result in the dysregulation of multiple organ systems. We also describe the importance of computational approaches, artificial intelligence and the analysis of big data to better characterize and recognize the interconnectedness of the various autonomic and non-autonomic symptoms. These techniques can lead to a better understanding of the progression of autonomic disorders, ultimately resulting in better care and management.